pymc-examples
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pymc-devs
Examples of PyMC models, including a library of Jupyter notebooks.
I looking forward to update the following example to the current pymc: "Getting started with PyMC4: Bayesian neural networks - Martin Krasser" https://nbviewer.org/github/krasserm/bayesian-machine-learning/blob/dev/bayesian-neural-networks/bayesian_neural_networks_pymc4.ipynb The example uses tensorflow and have the...
Addresses issues #135 and #137 and aims to advance it to Best Practices
File: https://github.com/pymc-devs/pymc-examples/blob/main/examples/gaussian_processes/GP-MaunaLoa.ipynb Reviewers: > The sections below may still be pending. If so, the issue is still available, it simply doesn't > have specific guidance yet. Please refer to [this...
**Introductory Overview of PyMC**: **https://www.pymc.io/projects/docs/en/latest/learn/core_notebooks/pymc_overview.html**: ## Issue description In the Model of Case Study 1 the local shrinkage prior $\tilde\lambda^2_i$ is specified as $\tilde \lambda^2_i = \frac{c^2*\lambda^2_i}{c^2 + \tau^2*\lambda^2_i}$. However...
Following quick discussion here https://github.com/pymc-devs/pymc-examples/issues/83#issuecomment-1159736382 we'll add the notebooks of core features (listed here https://www.pymc.io/projects/docs/en/stable/learn/core_notebooks/index.html) to the main set of examples here https://www.pymc.io/projects/examples/en/latest/gallery.html. Add as the first section in the...
File: https://github.com/pymc-devs/pymc-examples/blob/main/examples/generalized_linear_models/GLM-model-selection.ipynb Reviewers: > The sections below may still be pending. If so, the issue is still available, it simply doesn't > have specific guidance yet. Please refer to [this...
Addresses issue #134 and aims to advance it to best practices
https://github.com/pymc-devs/pymc3/pull/4815 changed how the `pm.Bound` API works, we need to find all instances where we use it and fix them.
https://docs.pymc.io/pymc-examples/examples/generalized_linear_models/GLM-hierarchical.html Missing are the images of the hierarchical model that @fonnesbeck created. Not sure if he has an updated link.